44 research outputs found
Predictive models for mutations in mismatch repair genes: implication for genetic counseling in developing countries
<p>Abstract</p> <p>Background</p> <p>Lynch syndrome (LS) is the most common form of inherited predisposition to colorectal cancer (CRC), accounting for 2-5% of all CRC. LS is an autosomal dominant disease characterized by mutations in the mismatch repair genes mutL homolog 1 (MLH1), mutS homolog 2 (MSH2), postmeiotic segregation increased 1 (PMS1), post-meiotic segregation increased 2 (PMS2) and mutS homolog 6 (MSH6). Mutation risk prediction models can be incorporated into clinical practice, facilitating the decision-making process and identifying individuals for molecular investigation. This is extremely important in countries with limited economic resources. This study aims to evaluate sensitivity and specificity of five predictive models for germline mutations in repair genes in a sample of individuals with suspected Lynch syndrome.</p> <p>Methods</p> <p>Blood samples from 88 patients were analyzed through sequencing MLH1, MSH2 and MSH6 genes. The probability of detecting a mutation was calculated using the PREMM, Barnetson, MMRpro, Wijnen and Myriad models. To evaluate the sensitivity and specificity of the models, receiver operating characteristic curves were constructed.</p> <p>Results</p> <p>Of the 88 patients included in this analysis, 31 mutations were identified: 16 were found in the MSH2 gene, 15 in the MLH1 gene and no pathogenic mutations were identified in the MSH6 gene. It was observed that the AUC for the PREMM (0.846), Barnetson (0.850), MMRpro (0.821) and Wijnen (0.807) models did not present significant statistical difference. The Myriad model presented lower AUC (0.704) than the four other models evaluated. Considering thresholds of ≥ 5%, the models sensitivity varied between 1 (Myriad) and 0.87 (Wijnen) and specificity ranged from 0 (Myriad) to 0.38 (Barnetson).</p> <p>Conclusions</p> <p>The Barnetson, PREMM, MMRpro and Wijnen models present similar AUC. The AUC of the Myriad model is statistically inferior to the four other models.</p
Mechanisms for inclusive governance
How mechanisms for inclusive governance are understood is built on the framing choices that are made about governance and that which is being governed. This chapter unpacks how governance can be understood and considers different historical and contemporary framings of water governance. A framing of “governance as praxis” is developed as a central element in the chapter. What makes governance inclusive is explored, drawing on theoretical, practical and institutional aspects before elucidating some of the different mechanisms currently used or proposed for creating inclusive water governance (though we argue against praxis based on simple mechanism). Finally, the factors that either constrain or enable inclusive water governance are explored with a focus on systemic concepts of learning and feedback
DISCUSSION of ""The implications of projected climate change for freshwater resources and their management"": Climate, hydrology and freshwater: Towards an interactive incorporation of hydrological experience into climate research
Climate, hydrology and freshwater: towards an interactive incorporation of hydrological experience into climate research
Concepção dos enfermeiros sobre o conteúdo do website sala de recuperação pós-anestésica
Clustering River Basins Using Time-Series Data Mining on Hydroelectric Energy Generation.
Hydropower is a significant renewable energy type with a considerable share in energy generation worldwide. As with the other common means of energy generation, hydropower is critical for the reliability and quality of electricity supply. Maintaining the reliability and quality of supply enables meeting the electricity demand of the loads adequately and efficient use of the energy resources, in addition to decreasing the related financial and environmental losses. In this paper, we target at the problem of basin clustering which is crucial for hydrological and electrical analyses regarding hydropower plants. We propose an approach based on time-series data mining on generation data of a large number of run-of-river type plants as well as of a number of representative storage type plants, in order to cluster the river basins in Turkey and present the clustering results with the related discussions. Based on these results, a new basin map is proposed which will be beneficial for enhanced hydrological and electrical analyses on hydropower and thereby for the maintenance of supply reliability and quality